A Computational Framework for Social Agents in Agent Mediated E-commerce

Agents that behave maliciously or incompetently are a potential hazard in open distributed e-commerce applications. However human societies have evolved signals and mechanisms based on social interaction to defend against such behaviour. In this paper we present a computational socio-cognitive framework which formalises social theories of trust, reputation, recommendation and learning from direct experience which enables agents to cope with malicious or incompetent actions. The framework integrates these socio-cognitive elements with an agent’s economic reasoning resulting in an agent whose behaviour in commercial transactions is influenced by its social interactions, whilst being motivated and constrained by economic considerations. The framework thus provides a comprehensive solution to a number of issues ranging from the evolution of a trust belief from individual experiences and recommendations to the use of those beliefs in market place level decisions. The framework is presented in the context of an artificial market place scenario which is part of a simulation environment currently under development. This is planned for use in evaluation of the framework, and hence can inform design of local decision making algorithms and mechanisms to enforce of social order in agent mediated e-commerce.